There are many ways to write DAX code to implement measures in the tabular model but writing improper DAX code may slow down the performance of the tabular model. I have encountered this problem during a recent tabular project implementation where, when you use conditional checking commands in DAX against a large number of rows, it may cause performance issues.

According to Gartner, the famous technology research group, 70% to 80% of Business Intelligence (BI) and data warehousing (DW) projects end up in the trash bin. BI projects often fail, incurring colossal losses to organizations. Why do DW/BI projects fail? What can organizations do to avoid pitfalls that cause DW/BI projects to fail?

Dynamic row-level security enables report authors to filter data based on the user roles. This prevents developers from having to maintain separate security matrices. This also avoids the complexity of maintaining users under different security roles.

Manual testing and automated testing can differ in many aspects. Manual testing ensures the software code does what is required, which consumes more time and effort. Also, manual testers must record their findings such as log files, external services, database errors.

During the last few weeks, I have been getting myself acquainted with Power BI and its features. Finding data sources (to practice with), cleaning them, creating data models, and creating reports and dashboards have been very interesting.

In some scenarios, to extend the functionality, we need to call external JAR files via StreamServe directly. In the article- Calling a java class from a StreamServe script, Stefan Cohen lucidly explains the process of calling
Java program through StreamServe.

Processes and Agility are vital for any software development company, irrespective of the maturity level; however, organizations sometimes lose the real Purpose of processes and agility, which is bringing Business Value to the organization. Let’s see how Processes, Agility, Purpose & Business Value come in to play in an ideal scenario.

Most software engineers spend unnatural working hours writing code for enterprise problems which, to be honest, is an industry cliché. Yes, deriving solutions for complex business problems can be the reward but after doing it for a few years one might want to consider broadening their domain especially in the arena of embedded systems.